Background: Malaria remains a significant public health concern in developing countries including Ethiopia. It is one cause of high-level of morbidity in Amhara region. Distinct geographical regions have different factors that influence malaria transmission. The study aims to forecasting malaria outbreaks by using empirical model developed in Amhara region, Ethiopia. Objective: To development and validation of an empirical model to predict malaria in Amhara National Regional State, Ethiopia, 2022. Method: A retrospective follow up study was conducted from Jan1/2016-Dec30/2021. A Total of 2448 malaria outbreak recorded were taken from 34 woredas. Data were transferred to Excel into SPSS version 25 and analyzed by R version 4.0.4. Bivariable logistic regression analysis was done, and the forecasting model was developed by backward stepwise multivariable logistic regression. Additionally time series seasonal decomposition was included .The best model was selected by likelihood ratio score, model accuracy was assessed by the area under the curve and calibration plot and internally validated by bootstrapping method. The results of significant predictors were reported as coefficients with their 95% confidence intervals. Result: The results showed that the presence of irrigation (OR = 1.522, 95% CI = 1.161-2.142), sunshine above the mean (SH>=7.167) (OR = 4.104 95%, CI = 1.706-9.791), rain fall above the mean (>=98.178)(OR = 21.73% CI = 5.755-141.326) and minimum temperate pressure (OR = 0.956, 95% CI = 0.956-0.997) were significantly associated with malaria outbreaks after adjustment for seasonality in Amhara region. The area under the curve for the original was 55.3.The model was validated by using boot strapping and it optimism coefficient was 1.618. . The p-value of the calibration belt was 0.798. Sensitivity and specificity of the model were 99.12% and 3.72% have respectively. Conclusion and recommendation: the study showed the possibility of forecasting malaria outbreak using climate and geographical factors. The model can help to forecast malaria outbreaks and to identify woredas at higher risk of having malaria outbreak. Also models have applications in malaria control and prevention activities. A prospective multicenter study should be conducted to confirm its accuracy and external validity. Key words, malarial outbreak, forecast, model, Ethiopia